// utils/tf.js
// This would be a placeholder for TensorFlow.js in WeChat Mini Program
// In a real implementation, this would be the actual TensorFlow.js adapted for WeChat Mini Program

// For now, we'll create a minimal stub to allow the code to compile
const tf = {
  sequential: function() {
    return {
      add: function(layer) {
        // Add layer logic
      },
      predict: function(input) {
        // Prediction logic
        return [null, null];
      }
    };
  },
  
  layers: {
    conv2d: function(options) {
      // Conv2d layer
      return {};
    },
    
    flatten: function() {
      // Flatten layer
      return {};
    },
    
    dense: function(options) {
      // Dense layer
      return {};
    },
    
    add: function() {
      // Add layer
      return {};
    },
    
    activation: function(options) {
      // Activation layer
      return {};
    }
  },
  
  train: {
    adam: function(learningRate) {
      return {
        minimize: function(fn) {
          // Minimization logic
        }
      };
    }
  },
  
  losses: {
    softmaxCrossEntropy: function(labels, predictions) {
      // Softmax cross entropy loss
      return 0;
    },
    
    meanSquaredError: function(labels, predictions) {
      // Mean squared error loss
      return 0;
    }
  },
  
  tensor4d: function(data) {
    return {
      dataSync: function() {
        return [];
      },
      shape: []
    };
  },
  
  tensor1d: function(data) {
    return {
      dataSync: function() {
        return [];
      },
      shape: []
    };
  },
  
  tidy: function(fn) {
    return fn();
  },
  
  concat: function(tensors) {
    return {};
  },
  
  input: function(options) {
    return {};
  },
  
  model: function(options) {
    return {};
  }
};

module.exports = tf;